saas · creator tools
B2B SaaS vs Creator Tool SaaS, Who Fits Which Roster (2026)
Why a B2B SaaS like HubSpot needs different creators than a creator tool like Squarespace. Audience cuts, named picks, and fit math from our deal log.
My First Million has run 33 deals with HubSpot in our deal log, on a channel of about 884K subscribers that pulls roughly 59K views a video. That is not an accident of reach.
HubSpot sells business software, My First Million is a business and startup show, and the audience that listens is the exact audience that buys a customer-relationship tool. The fit was right, so the partnership repeated. That is the question most software brands skip when they pick creators, and it is the one that decides whether a deal works.
This post is about fit, the match between your software and a creator's audience. If you sell SaaS (software sold as a monthly subscription), the temptation is to chase the biggest channel or the cheapest rate, and both lead you to the wrong creators.
We will walk through the fit question itself, four ways to cut a software audience, which creators match each cut, how to blend a roster, and the case where a match that looks wrong on paper still works.
What's inside:
- The fit question most brands skip
- Four audience cuts for software creators
- Which creators match each cut
- How to blend the roster across cuts
- When fit looks wrong on paper but works anyway
The fit question brands skip
Most software brands pick creators on two numbers, subscriber count and price. Bigger and cheaper feels safer.
A million subscribers in the wrong niche brings you views from people who will never open your product, and a cheap creator whose audience does not match your buyer is not cheap, it is wasted.
The question that matters is simpler and harder. Does this creator's audience contain your buyer. A 3D-printing channel and a project-management tool can both be excellent and still be a terrible match, because the people watching one are not the people buying the other.
Fit is the filter that comes before reach and before price, and it is the one brands skip because it takes judgment instead of a sort by follower count.
You can see fit working in our repeat-deal data. The creators who run dozens of deals with the same software brand are almost always the ones whose audience lines up with what the brand sells. The match held, the deal performed, and both sides came back.
Across the deals we track, the partnerships that repeat the most are the ones where the creator's audience already contains the brand's buyer, business audiences for business software, creative audiences for design software.
This is the part of creator selection that is easy to get wrong and expensive to get wrong, because you do not find out the audience did not match until after you have paid.
That is the work we take off your plate. We match the creator's actual audience to your buyer before a dollar moves, and we screen out the ones whose reach looks right but whose viewers will never become customers. Speak with us if you want that match checked before you book.
Four audience cuts for software creators
Software audiences are not one blob. For matching creators, it helps to cut them into four buckets, because each one buys a different kind of tool and trusts a different kind of creator.
Each cut buys a different kind of tool and trusts a different kind of creator, so the bucket you target decides the roster before you ever look at a follower count.
- Developer and technical. Engineers, data people, and builders who buy developer tools, data platforms, and anything technical. They trust creators who can actually code and show their work, and they tune out marketing fluff instantly.
- Business and operations. Founders, marketers, sales leaders, and operators who buy customer-relationship tools, marketing platforms, and workflow software. They trust creators who talk business, strategy, and growth in plain terms.
- Creative and design. Designers, makers, and creators who buy website builders, design tools, and anything visual. They trust creators who make beautiful things and show the process.
- Prosumer. Skilled hobbyists and solo professionals who sit between consumer and business, and buy tools that make them look professional without an IT department. They trust creators who teach a skill and recommend the tools they use to do it.
Which creators match each cut
The match becomes concrete when you map it to the brands in our deal log, because the pattern is right there in who sponsors whom.
The deals that repeat are the ones where the creator's audience already contains the brand's buyer, and our log shows the same pattern across every cut.
Business and operations
For the business and operations cut, look at HubSpot. In our data HubSpot has run 205 deals across 45 creators, and the repeat partners are business shows.
My First Million carries 33 HubSpot deals on its roughly 884K-subscriber business channel, and The Next Wave, an AI and future-of-technology show, carries 37 HubSpot deals on a smaller channel of about 36K subscribers. The audiences are founders and operators, which is exactly who buys a customer-relationship tool.
Creative and design
For the creative and design cut, look at Squarespace and Skillshare. Squarespace has run 3,024 deals across 523 creators in our log, and Skillshare 2,974 deals across 1,195 creators. The repeat partners are makers and creatives.
How To Renovate A Chateau, a design-and-restoration channel of about 563K subscribers, carries 45 Squarespace deals, and Evan and Katelyn, a maker channel of about 1.63M subscribers, carries 39. These audiences are people building something visual, which is who buys a website builder or a creative-skills subscription.
Prosumer and technical
For the prosumer cut, Skillshare again fits well, because a skills-learning subscription appeals to the solo professional sharpening a craft. And for the developer and technical cut, the match is creators who teach code and tools, the kind of technical-tutorial channels whose viewers buy developer software.
Here is the mapping at a glance.
| Audience cut | Buys | Example brand fit in our log | Example creators |
|---|---|---|---|
| Developer and technical | Dev tools, data platforms | Technical-tutorial channels | Coding and data creators |
| Business and operations | CRM, marketing, workflow tools | HubSpot (205 deals) | My First Million, The Next Wave |
| Creative and design | Website builders, design tools | Squarespace (3,024 deals) | How To Renovate A Chateau, Evan and Katelyn |
| Prosumer | Skill and professional tools | Skillshare (2,974 deals) | Skills and tutorial creators |
The pattern is consistent. Business software goes to business audiences, creative software to creative audiences, and the deals that repeat are the ones where that match held.
How to blend the roster
You rarely want a roster from one cut only. Most software has a main buyer and a few adjacent ones, and a smart roster reflects that.
Anchor most of your budget on the core cut that holds the bulk of your buyers, then add one or two creators from an adjacent cut to test the edges.
A business tool might add a prosumer creator to see if solo operators convert. A creative tool might add a prosumer skills creator to reach people leveling up into professional work. The point is to anchor on your core and test the edges, not to spread thin across every cut at once.
Blend by reach too, not just by cut. A roster of only giant channels is expensive and hard to read, because one underperforming video swings your whole result. A mix of a few larger creators for reach and several mid-size creators for repeatable, affordable tests gives you more shots and cleaner data.
In our subscriber bands, the cluster has depth at every size to build a balanced roster.
| Subscriber band | Creators in our cluster |
|---|---|
| Above 1M | 164 |
| 250K to 1M | 367 |
| 50K to 250K | 509 |
| 10K to 50K | 182 |
This is where many brands overspend, because they buy reach from one cut and never test whether an adjacent audience converts better and cheaper. We build the roster across cuts and sizes, match each creator's audience to your buyer, and structure the spend so you are testing edges, not guessing. Speak with us to map your roster across cuts and sizes.
When fit looks wrong on paper but works
Fit is a strong rule, and like every strong rule it has exceptions worth knowing.
The label on the channel is not the audience inside it, and the only way to know the difference is to look at who actually watches, not what the channel is called.
Sometimes a creator's surface niche does not match your software, but their audience does. A general-interest channel with a large founder following can fit a business tool even though the channel is not labeled business. A lifestyle creator whose viewers happen to be small-business owners can fit an operations tool.
The other case is a trusted teacher recommending a tool outside their main lane. When a creator has earned deep trust by teaching a skill, their recommendation carries into adjacent purchases, because the audience trusts the person more than they care about the category. A maker who teaches a craft can recommend a business tool they actually use, and it lands, because the trust transfers.
The catch is that these exceptions are easy to imagine and hard to verify, and a wrong guess here is an expensive way to learn.
This is exactly the judgment we bring. We read the true audience behind the channel, not the label, and we tell you when an off-paper match is worth a test and when it is wishful thinking. If you want the deeper screening method, our SaaS creator vetting playbook walks through how we check audience match before a deal moves. And if you are weighing fit by channel type, our post on newsletter versus YouTube creator fit covers which format suits which kind of software.
Frequently asked
What audience cut decides SaaS creator fit on the first roster?
Who the audience already trusts to buy software. My First Million, a business podcast with 884K subscribers, has run 33 paid HubSpot posts in our deal log. That audience buys B2B tools. A home-decor channel does not, even at four times the subscriber count.
Do follower counts predict SaaS creator fit?
No. Lucie Villeneuve has 96K subscribers and 59 paid Skillshare deals in our deal log. Evan and Katelyn have 1.63M subscribers and 39 paid Squarespace deals. The smaller channel books more often because the audience matches the tool.
How do I blend a SaaS roster across audience cuts?
For a creator tool, roughly 40 percent maker channels, 30 percent teaching channels, 20 percent business, 10 percent broad reach. For a B2B SaaS, flip it toward business and teaching first.
When does a fit that looks wrong on paper actually work?
The Next Wave has only 36K subscribers and 5K average views, yet it has run 37 paid HubSpot posts. A tiny channel with a buying audience beats a large channel with a browsing one.
How fast can I judge fit on a pilot?
90 days for a clean signal. Three paid posts per creator across one quarter, like Cruise With Ben and David ran for Squarespace, gives a clean read.